CN115728276B

CN115728276B - Explosive detection method and detection system

Info

Publication number: CN115728276B
Application number: CN202211419359.3A
Authority: CN
Inventors: 刘宁; 蔡庸军; 李明勇; 兰江; 尤兴志
Original assignee: Csic Anpel Instrument Co ltd Hubei
Current assignee: Csic Anpel Instrument Co ltd Hubei
Priority date: 2022-11-14
Filing date: 2022-11-14
Publication date: 2024-01-23
Anticipated expiration: 2042-11-14
Also published as: CN115728276A

Abstract

The embodiment of the application discloses an explosive detection method and an explosive detection system, which eliminate interference of a fluorescent background after a multichannel fluorescent signal of an explosive is obtained, then perform signal preprocessing to reduce interference of impurities in the fluorescent signal, process the fluorescent signal by adopting a fluorescent signal compensation algorithm, a K value solving algorithm and a characteristic value characterization algorithm to obtain a characteristic value of the explosive, and then compare the characteristic value with the characteristic value in a substance characteristic library so as to pre-judge the type of the explosive. The method eliminates the interference of fluorescent background, mixed signals and the like, and improves the accuracy of explosive detection.

Description

Explosive detection method and detection system

Technical Field

The application relates to the field of explosive fluorescence detection, in particular to an explosive detection method and an explosive detection system.

Background

The fluorescent explosive detector can detect whether the to-be-detected substance contains the explosive or not by using a fluorescent detection technology (Mass spectrometry, MS), and the detection principle is as follows. The fluorescent explosive detector is internally provided with a fluorescent material, and when the fluorescent material is excited by excitation light with a certain wavelength, an original fluorescent signal with a certain wavelength and intensity can be generated. When detecting a substance to be detected by using a fluorescent explosive detector, if the substance to be detected contains an explosive, after the explosive contacts a fluorescent material, the fluorescent material is excited by excitation light with the same wavelength, and the fluorescent material changes in fluorescence intensity, wavelength, peak position or the like to generate a new fluorescent signal, for example, quenching or enhancement of the fluorescence intensity relative to the original fluorescent signal occurs. These new fluorescent signals can be captured by the detection device of the fluorescent explosives detector to detect the corresponding types of explosives. The above process involves analysis of the fluorescent signal, however, the noise of the fluorescent signal obtained by the current fluorescent explosive detector is too loud, and the fluorescent signal is disturbed too strongly, so that the judgment of the type of the explosive is not accurate.

Disclosure of Invention

The embodiment of the application provides an explosive detection method and an explosive detection system, which are used for solving the problem that the existing fluorescent explosive detector is inaccurate in judging the type of explosives.

To achieve the above object, the present application provides a method for detecting explosives, which includes:

collecting fluorescence intensity signals of a plurality of fluorescence channels of the fluorescent explosive, converting the fluorescence intensity signals into digital fluorescence signals, and calculating a fluorescence response value of the fluorescent explosive;

eliminating the fluorescent background of the fluorescent response value to obtain a net fluorescent signal;

carrying out signal pretreatment on the net fluorescent signal to obtain a pretreated signal;

and (3) performing fluorescent signal compensation algorithm, K value solving algorithm and characteristic value characterization algorithm processing on the preprocessed signals, and pre-judging the types of fluorescent explosives according to characteristic value comparison algorithm.

In some embodiments, multiple ADS1255 sampling chips are alternately driven by SPI chip-select driving to collect fluorescence intensity signals of multiple fluorescence channels.

In some embodiments, the process of eliminating includes:

smoothing the fluorescence response value to eliminate high-frequency white noise and obtain a smooth fluorescence signal;

Obtaining the minimum value in each window range in the smooth fluorescent signal, obtaining the position of the maximum value between two minimum values according to the minimum values of two adjacent window ranges, and dividing the signal section covered by the two adjacent window ranges in the smooth fluorescent signal into a left signal section and a right signal section according to the position of the maximum value;

subtracting the minimum value from the left signal segment to obtain a left zeroing signal segment, and subtracting the minimum value from the right signal segment to obtain a right zeroing signal segment;

and selecting the higher signal segment in the left return-to-zero signal segment and the right return-to-zero signal segment, multiplying the higher signal segment by the scaling coefficient f, and then respectively performing adaptive signal scaling to obtain a net fluorescent signal.

In some embodiments, the formula for the scaling factor f is:

wherein f _max The maximum value in the left signal section and the right signal section is a maximum value in the left return-to-zero signal section and the right return-to-zero signal section.

In some embodiments, the adaptive signal scales as: after the left return-to-zero signal segment or the right return-to-zero signal segment is multiplied by the scaling factor f, the following calculations are performed, respectively:

wherein x is _i For each data value in the left return-to-zero signal segment or the right return-to-zero signal segment, n is the size of the data set of the left return-to-zero signal segment or the right return-to-zero signal segment.

In some embodiments, the signal preprocessing includes zero-averaging processing and normalization processing.

In some embodiments, a method of zero-averaging processing includes:

according to the number num of data of the net fluorescence signal and each data value x _i Obtaining the mean value u= (x) of the net fluorescence signal ₁ +x ₂ +…+x _i )/num；

Calculation markDifference of accuracy

Zero-mean processingA zero-averaged signal is obtained.

In some embodiments, a method of normalizing processing includes:

obtaining the maximum value min (x _i ) And minimum value min (x _i ) Passing each data value of the zero-averaged signal throughScaling to between 0 and 1, resulting in a preprocessed signal.

In some embodiments, the fluorescence signal compensation algorithm comprises: each data value x of the pre-processed signal _ii Substituting into fluorescent signal compensation formulaObtaining a compensated signal x _ii 'A'; t is the ambient temperature at the time of detection.

In some embodiments, the K-value solving algorithm is according to the following relationshipSolving a K value; wherein I is _F Representing the original fluorescent signal, I _O Representing a fluorescent reference signal, A _T Represents the fluorescence wavelength at the current temperature, τ represents the fluorescence absorbance, x represents the multiplication, +.>Indicating the fluorescence quenching rate. The original fluorescent signal refers to a fluorescent signal when no explosives are introduced, i.e. a fluorescent signal obtained when the explosives are not in contact with the fluorescent material. The fluorescence reference signal is a preset fluorescence signal value and is used for eliminating systematic errors such as measurement errors and the like. The fluorescence wavelength at the current temperature means that at the current The wavelength of the fluorescence emitted by the fluorescent explosive when the explosive is in contact with the fluorescent material at the temperature is measured. The fluorescence absorption rate is the device performance of the fluorescence detection instrument, and can be set to different values according to different measurement conditions or empirically. The fluorescence quenching rate may be set to different values according to different measurement conditions or empirically. Of course, there are other methods of setting the fluorescence absorptance and the fluorescence quenching rate.

In some embodiments, the eigenvalue characterization algorithm is based on the compensated signal x _ii ' and K values calculate the characteristic value z of the fluorescent explosive _i ' the calculation formula is as follows: z _i ′*E[K*x _ii ′]-A|, where E represents the average value and A represents the compensated signal x _ii ' inverse of the formed signal matrix. Because of the compensated signal x _ii The' number is large so that one signal matrix can be formed, and a is the inverse of the signal matrix.

In some embodiments, the eigenvalue comparison algorithm compares the eigenvalue z _i And (3) comparing the characteristic value Z with a characteristic value Z in a pre-established substance characteristic library, if a comparison result is obtained, obtaining the type of the fluorescent explosive, and if the comparison result is not obtained, indicating that the fluorescent explosive is not present.

In some embodiments, the method of creating a library of material characteristics includes obtaining a room temperature signal characteristic value Z _r Step (1) of obtaining a characteristic value Z of a high-temperature signal _h Step (a) of obtaining a low-temperature signal characteristic value Z _l Is a step of fitting.

In some embodiments, a room temperature signal characteristic value Z is obtained _r The method comprises the following steps:

respectively collecting multiple fluorescent explosives at room temperature T _r The fluorescent intensity signals of the fluorescent channels are converted into digital fluorescent signals;

eliminating the fluorescent background of the digital fluorescent signal to obtain a net fluorescent signal;

and carrying out signal pretreatment on the net fluorescent signal to obtain a pretreated signal. When the substance characteristic library is constructed, the fluorescence data is standard value and does not deviate, so that the pretreatment processes of fluorescence signals such as a fluorescence signal compensation algorithm, a K value solving algorithm and the like are not needed in the construction of the substance characteristic library.

Calculating the room temperature signal characteristic value Z corresponding to various fluorescent explosives according to the following formula _r ：

Wherein Z is _r For the room temperature signal characteristic value, i is one data set of the pre-processed signal, j is another data set of the pre-processed signal measured again after i, s is the time for obtaining one data set, and s is given in min, T _r T is the temperature at room temperature _r In units of °c.

In some embodiments, the high temperature signal characteristic value Z is obtained _h The method comprises the following steps:

respectively collecting multiple fluorescent explosives at high temperature T _h The fluorescent intensity signals of the fluorescent channels are converted into digital fluorescent signals;

calculating the characteristic value Z of the high-temperature signal corresponding to various fluorescent explosives according to the following formula _h ：

Wherein Z is _h For the characteristic value of the high-temperature signal, i is one data set of the pre-processed signal, j is another data set of the pre-processed signal which is re-measured after i, s is the time for obtaining one data set, and the unit of s is min and T _h T is the temperature at high temperature _h In units of °c.

In some embodiments, the low temperature signal characteristic value Z is obtained _l The method comprises the following steps:

respectively collecting multiple fluorescent explosives at low temperature T _l The fluorescent intensity signals of the fluorescent channels are converted into digital fluorescent signals;

Calculating low-temperature signal characteristic values Z corresponding to various fluorescent explosives according to the following formula _l ：

Wherein Z is _l For the characteristic value of the low-temperature signal, i is one data set of the pre-processed signal, j is another data set of the pre-processed signal which is re-measured after i, s is the time for obtaining one data set, and the unit of s is min and T _l T is the temperature at low temperature _l In units of °c.

In some embodiments, the fitting step is to fit the room temperature signal characteristic value Z _r Characteristic value Z of high temperature signal _h Low temperature signal characteristic value Z _l Fitting to a library of material characteristics.

The embodiment of the application also provides an explosive detection system, which comprises:

the multichannel signal acquisition unit acquires fluorescence intensity signals of a plurality of fluorescence channels of the fluorescent explosive, converts the fluorescence intensity signals into digital fluorescence signals and calculates a fluorescence response value of the fluorescent explosive;

the signal preprocessing unit is used for eliminating a fluorescent background of the fluorescent response value to obtain a net fluorescent signal; carrying out signal pretreatment on the net fluorescent signal to obtain a pretreated signal;

the signal characterization unit is used for carrying out fluorescent signal compensation algorithm, K value solving algorithm and characteristic value characterization algorithm processing on the preprocessed signals to obtain the characteristic value z of the fluorescent explosive _i ′；

Substance detection algorithm unit for comparing characteristic value z with characteristic value comparison algorithm _i And (3) comparing the characteristic value Z with a characteristic value Z in a pre-established substance characteristic library, if a comparison result is obtained, obtaining the type of the fluorescent explosive, and if the comparison result is not obtained, indicating that the fluorescent explosive is not present.

In some embodiments, the explosives detection system further comprises a central processing unit in communication with the multi-channel signal acquisition unit, the signal pre-processing unit, the signal characterization unit, and the material detection algorithm unit, respectively.

The explosives detection system further includes: and the audible and visual alarm unit generates audible and visual alarm signals when the types of fluorescent explosives are obtained.

In some embodiments, the explosives detection system further comprises a build species library unit, the build species library unit comprising:

the room temperature characteristic value acquisition module acquires a room temperature signal characteristic value Z according to the respectively acquired fluorescence intensity signals of a plurality of fluorescence channels of a plurality of fluorescent explosives at room temperature Tr _r ；

The high-temperature characteristic value acquisition module is used for acquiring a plurality of fluorescent explosives at a high temperature T according to the acquired fluorescent explosives respectively _h Obtaining high-temperature signal characteristic value Z by using fluorescence intensity signals of a plurality of fluorescence channels _h ；

The low-temperature characteristic value acquisition module is used for acquiring a plurality of fluorescent explosives at a low temperature T according to the acquired fluorescent explosives respectively _l Obtaining low-temperature signal characteristic value Z by using fluorescence intensity signals of a plurality of fluorescence channels _l ；

Fitting module for fitting room temperature signal characteristic value Z _r Characteristic value Z of high temperature signal _h Low temperature signal characteristic value Z _l Fitting to a library of material characteristics.

Due to the adoption of the technical scheme, the application has the following technical effects:

the application discloses an explosive detection method and an explosive detection system, which eliminate interference of a fluorescent background after a multichannel fluorescent signal of an explosive is obtained, then perform signal pretreatment, reduce interference of impurities in the fluorescent signal, process the fluorescent signal by adopting a fluorescent signal compensation algorithm, a K value solving algorithm and a characteristic value characterization algorithm, obtain a characteristic value of the explosive, and then compare the characteristic value with the characteristic value in a substance characteristic library, so that the type of the explosive is pre-judged. The method eliminates the interference of fluorescent background, mixed signals and the like, and improves the accuracy of explosive detection.

Drawings

The present application is further described below with reference to the accompanying drawings.

Fig. 1 is a block diagram of an explosives detection system in an embodiment of the application.

Fig. 2 is a flowchart of a detection method according to an embodiment of the present application.

Fig. 3 is a flowchart of library creation according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure. In the description of the present application, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," etc., as used herein, indicate or relate to an orientation or position as shown in the drawings, merely for convenience of description and to simplify the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be configured and operated in a particular orientation, and thus should not be construed as limiting the present application.

The embodiment of the application provides a method for detecting explosives, which comprises the following steps:

(1) Collecting fluorescence intensity signals of a plurality of fluorescence channels of the fluorescent explosive, converting the fluorescence intensity signals into digital fluorescence signals and calculating a fluorescence response value of the fluorescent explosive;

(2) Eliminating the fluorescence background of the fluorescence response value to obtain a net fluorescence signal;

(3) Performing signal preprocessing on the net fluorescent signal to obtain a preprocessed signal;

(4) And performing fluorescent signal compensation algorithm, K value solving algorithm and characteristic value characterization algorithm processing on the preprocessed signals, and pre-judging the types of fluorescent explosives according to the characteristic value comparison algorithm.

Wherein in step (1), the fluorescent explosive is a substance formed after the fluorescent material in the fluorescent explosive detection instrument is contacted with the explosive. The fluorescent material emits a fluorescent signal after the explosives are contacted, and the ADS1255 sampling chip is adopted to collect the fluorescent signal. The ADS1255 sampling chip is an SPI driving mode of the singlechip. Specifically, a plurality of ADS1255 sampling chips are alternately driven by an SPI chip selection driving mode to collect fluorescence intensity signals of a plurality of fluorescence channels, and the fluorescence intensity signals are converted from analog fluorescence signals to digital fluorescence signals. Step (1) may be performed using a multi-channel signal acquisition unit. The multi-channel comprises two or more channels, which can be three channels, four channels, five channels and eight channels at most.

In the step (1), the multi-channel acquisition principle is that an ADS1255 high-precision chip is adopted as a medium for acquiring digital fluorescent signals of fluorescent explosives, fluorescent intensity signals (namely multi-channel fluorescent signal data) of a plurality of fluorescent channels are acquired in an SPI alternating driving mode, and after the fluorescent intensity signals of the fluorescent explosives of the plurality of fluorescent channels are acquired, the fluorescent intensity signals are calculated according to the corresponding characteristics of each fluorescent explosive, so as to acquire a fluorescent response value of the corresponding fluorescent explosive. The calculation process is calculated according to the sampled voltage value and the intensity of the digital fluorescence signal.

In the step (2), the fluorescent background elimination is to find spectral characteristic peaks of the fluorescent intensity signals of the explosives, and eliminate some larger fluorescent background signals overlapped by the characteristic peaks, so that better fluorescent spectral data can be obtained by reducing, especially for some weaker fluorescent intensity reaction peaks, and the signal change is more obvious. The process of fluorescent background elimination includes:

(2-1) smoothing the fluorescence response value to eliminate high-frequency white noise and obtain a smooth fluorescence signal;

(2-2) obtaining the minimum value in each window range in the smooth fluorescence signal, obtaining the position of the maximum value between two minimum values according to the minimum values of two adjacent window ranges, and dividing the signal section covered by the two adjacent window ranges in the smooth fluorescence signal into a left signal section and a right signal section according to the position of the maximum value;

(2-3) subtracting the minimum value from the left signal segment to obtain a left zeroing signal segment, and subtracting the minimum value from the right signal segment to obtain a right zeroing signal segment;

(2-4), selecting the higher signal segment in the left return-to-zero signal segment and the right return-to-zero signal segment, multiplying the higher signal segment by the scaling coefficient f, and then respectively performing adaptive signal scaling to obtain a net fluorescent signal.

Wherein the main purpose of step (2) is to remove the fluorescent background signal, which employs a fluorescent background cancellation algorithm (adaptive wavelet). The fluorescence background elimination algorithm is used for eliminating fluorescence background signals superimposed by fluorescence characteristic peaks, so that better fluorescence spectrum data can be obtained, the change of the fluorescence signals is more obvious, and the accuracy is higher when signal characterization is carried out later. Because the signal of the fluorescent explosive needs to have the characteristics of small interference, single signal representation and the like, the application adopts the adaptive wavelet to filter the fluorescent response value after obtaining the fluorescent response values of the fluorescent explosive of a plurality of fluorescent channels so as to reduce the interference of background noise signals.

In step (2-2), the size of the coverage of each window range in the smoothed fluorescence signal may be arbitrarily specified for the sake of convenience of calculation. In addition, the left signal section and the right signal section are selected according to two adjacent window ranges, so that the left signal section and the right signal section cover the window range of each signal peak together. The algorithm adopts a variable-length window cutting method to process, the data in different window ranges are re-divided according to the minimum value, and finally calculation is carried out according to the window ranges after re-division, so that signals which are irrelevant to material analysis and influence the material analysis, such as a substrate of a fluorescent signal, a change process signal, abrupt change during time sequence switching and the like, are eliminated, and the accuracy and the sensitivity of analysis are improved.

In step (2-3) two discrete data segments are obtained, i.e. the left and right return-to-zero signal segments each exhibit the characteristics of a discrete data segment, since the minimum value is subtracted from the value.

In step (2-4), the formula of the proportionality coefficient f is:

In step (2-4), the adaptive signal scales to: after the left return-to-zero signal segment or the right return-to-zero signal segment is multiplied by the scaling factor f, the following calculations are performed, respectively:

wherein x is _i For each data value in the left or right return-to-zero signal segment, n is the size of the data set of the left or right return-to-zero signal segment (i.e., the number of data contained in each signal segment).

In step (3), the signal preprocessing includes zero-averaging processing and normalization processing. The signal preprocessing aims to reduce interference signals included in fluorescent signals, and can reduce errors of fluorescent intensity signals (for example, errors caused by large differences between the fluorescent intensity signals and arrays can be reduced), so that the fluorescent intensity signals are more accurate, and the signal preprocessing method mainly comprises a centering algorithm and a normalization algorithm.

In step (3), the method of zero-mean processing (centering algorithm) includes:

Calculate standard deviation

Zero-mean processingResulting in a zero-averaged signal (i.e., a normalization algorithm).

Because the signals of each channel collected by the fluorescent explosive detection instrument are not only fluorescent signals of the reactive explosive, but also substrate signals, change process signals and time sequence switching mutation signals (because the fluorescent signals obtained by the fluorescent explosive detection instrument are the same as the driving time sequence of the light source), zero mean value and standard deviation are adopted to process the fluorescent signals so as to remove the signals which are irrelevant to and influence the material analysis, such as the substrate of the fluorescent signals, the change process signals, the mutation during time sequence switching, and the like, so that the accuracy and the sensitivity of the analysis are improved.

In step (3), the normalization processing method includes:

And (4) judging the types of the explosives by adopting a material detection algorithm, wherein the material detection algorithm comprises a fluorescent signal compensation algorithm, a K value solving algorithm, a characteristic value characterization algorithm, a characteristic value comparison algorithm and the like, and finally judging the types of the fluorescent explosives in advance. The substance detection algorithm is a comprehensive algorithm of detection states of the fluorescent explosive detection instrument and explosive type detection logic, and can carry out comprehensive logic judgment on responses of different explosives according to the states of the fluorescent explosive detection instrument and fluorescent signals, so that the detection of the fluorescent explosive detection instrument on the explosive type is completed.

In step (4), the fluorescence signal compensation algorithm includes: each data value x of the pre-processed signal _ii Substituting into fluorescent signal compensation formulaObtaining a compensated signal x _ii 'A'; t is the ambient temperature at the time of detection.

In step (4), the K-value solving algorithm is based on the following relationSolving a K value; wherein I is _F Representing the original fluorescent signal, I _O Representing a fluorescent reference signal, A _T Represents the fluorescence wavelength at the current temperature, τ represents the fluorescence absorbance, x represents the multiplication, +.>Indicating the fluorescence quenching rate. The original fluorescent signal refers to a fluorescent signal when no explosives are introduced, i.e. a fluorescent signal obtained when the explosives are not in contact with the fluorescent material. The fluorescence reference signal is a preset fluorescence signal value and is used for eliminating systematic errors such as measurement errors and the like. The current temperature fluorescence wavelength refers to the wavelength of fluorescence emitted by the fluorescent explosives when they are in contact with the fluorescent material at the current measurement temperature. The fluorescence absorption rate is the device performance of the fluorescence detection instrument, and can be set to different values according to different measurement conditions or empirically. The fluorescence quenching rate may be set to different values according to different measurement conditions or empirically. Of course, there are other methods of setting the fluorescence absorptance and the fluorescence quenching rate.

In step (4), the eigenvalue characterization algorithm is based on the compensated signal x _ii ' and K values calculate the characteristic value z of the fluorescent explosive _i ' the calculation formula is as follows: z _i ′*E[K*x _ii ′]-A|, where E represents the average value and A represents the compensated signal x _ii ' inverse of the formed signal matrix. Because of the compensated signal x _ii The' number is large so that one signal matrix can be formed, and a is the inverse of the signal matrix.

In the step (4), the eigenvalue comparison algorithm compares the eigenvalue z _i And (3) comparing the characteristic value Z with a characteristic value Z in a pre-established substance characteristic library, if a comparison result is obtained, obtaining the type of the fluorescent explosive, and if the comparison result is not obtained, indicating that the fluorescent explosive is not present. And (4) judging the type of the fluorescent explosive as a pre-judgment, and carrying out final judgment by combining other algorithms. Since the temperature value deviates from the temperature point in the process of warehouse establishment in the actual detection, the type of the explosive is pre-judged in the process of detecting the substance.

In the material detection algorithm, the material detection algorithm carries out algorithm processing on the reactions of different explosives and fluorescent materials, fixes the detection limit priority and the identification time of the explosives, and enlarges the difference of the represented signal characteristics of the explosives passing through the fluorescent materials, so that the fluorescent explosive detection instrument can accurately and rapidly detect the results.

In step (4), the substance detection algorithm further comprises a multi-channel signal alternating response identification logic algorithm. The algorithm is used for carrying out final judgment by combining the pre-judgment result of the type of the fluorescent explosive. The judgment principle of the multichannel signal alternating response identification logic algorithm is as follows: locking the range of the types of the fluorescent explosives according to the pre-judging result of the types of the fluorescent explosives, and finally judging the explosives through the fluorescent signal cross response recognition algorithm of each channel, wherein the main method comprises the following steps:

1. setting the value of a threshold value P, and judging whether each channel reaches a response limit according to the threshold value P. The threshold P is compared with the magnitude of the fluorescence response value. If the magnitude of the fluorescence response exceeds the threshold value P, this indicates that the fluorescence response obtained by the channel is incorrect and needs to be discarded or re-measured.

2. And acquiring all channels which do not reach the response limit, and acquiring the explosive type range through the peak outlet time T of all channels and the signal peak intensity of all channels.

3. Combining the eigenvalues z _i ' library comparison is performed to narrow the range of explosive species.

4. And comprehensively judging the characteristic value comparison result and the response priority of various explosives to obtain a detection result.

The characteristic value comparison algorithm in the step (4) further comprises a method for establishing a substance characteristic library in the step (5). The method for establishing the substance characteristic library comprises the steps of obtaining a room temperature signal characteristic value Z _r Step (1) of obtaining a characteristic value Z of a high-temperature signal _h Step (a) of obtaining a low-temperature signal characteristic value Z _l Is a step of fitting.

In the step (5), the conventional substance library only considers the signal intensity corresponding to different substances, but does not consider the time of the signal response of the substances and the parameters of the fluorescent explosive detection instrument, and the substance characteristic library established by the application combines the parameters of the fluorescent explosive detection instrument such as high temperature (40 ℃), low temperature (-20 ℃), flow, signal response time and the like, so that the working environment of the fluorescent explosive detection instrument and the aging degree of the fluorescent explosive are fully considered, and the accuracy of substance identification can be better improved.

Wherein, (5-1) the room temperature signal characteristic value Z is obtained _r The method comprises the following steps:

Wherein Z is _r I is the primary data set of the signal after pretreatment, j is the characteristic value of the room temperature signalAnother sub-data set of the pre-processed signal re-measured after i, s being the time for obtaining the sub-data set, s being in min, T _r At room temperature (i.e., normal temperature), T _r In units of °c. The data set can be acquired more than twice (generally even number of times) in the application, so as to avoid errors caused by acquiring the data set once. The following is the same.

(5-2) obtaining the characteristic value Z of the high temperature signal _h The method comprises the following steps:

Wherein Z is _h For the characteristic value of the high-temperature signal, i is one data set of the pre-processed signal, j is another data set of the pre-processed signal which is re-measured after i, s is the time for obtaining one data set, and the unit of s is min and T _h T is the temperature at high temperature (room temperature +40℃), T _h In units of °c.

(5-3) obtaining the characteristic value Z of the low-temperature signal _l The method comprises the following steps:

according to the following formulaCalculating low-temperature signal characteristic values Z corresponding to various fluorescent explosives _l ：

Wherein Z is _l For the characteristic value of the low-temperature signal, i is one data set of the pre-processed signal, j is another data set of the pre-processed signal which is re-measured after i, s is the time for obtaining one data set, and the unit of s is min and T _l T is the temperature at low temperature (room temperature-20 ℃) _l In units of °c.

(5-4) fitting the room temperature signal characteristic value Z _r Characteristic value Z of high temperature signal _h Low temperature signal characteristic value Z _l Fitting to a library of material characteristics. The fitting process is as follows: and respectively acquiring three characteristic values of each fluorescent explosive at room temperature, high temperature and low temperature, and fitting a smooth characteristic curve based on the corresponding relation between the three characteristic values and the three temperatures, wherein the characteristic curve can cover the characteristic values of each fluorescent explosive at different temperatures. The characteristic curves corresponding to various fluorescent explosives one by one can be fitted, so that the substance characteristic library comprises a plurality of characteristic curves, and the types of the explosives corresponding to the fluorescent signals can be obtained from the substance characteristic library according to the environmental temperature values and the calculated characteristic values when the fluorescent signals are measured during characteristic comparison.

The material detection algorithm of the embodiment of the application comprises signal compensation, K value solving, material pre-judging, library ratio and the like. According to the method and the device, the fluorescent signals are compensated according to the temperature, humidity, air pressure and other parameters of the environment where the instrument is located, so that the instrument is prevented from being located in different environments, and the signal response and the substance characteristic library have larger deviation when detecting explosives.

In addition, in order to be able to rapidly and accurately identify various explosives, a substance characteristic library is established for the explosives to be tested under different environmental conditions, meanwhile, when the explosives are identified, different explosives are pre-judged through an algorithm, a preliminary identification result of the detected explosives is given, then specific explosive types are identified through an alternate response identification algorithm among channels, and erroneous judgment of the explosives is prevented.

As shown in fig. 1, an embodiment of the present application further provides an explosive detection system, which includes the following units: the device comprises a multichannel signal acquisition unit, a signal preprocessing unit, a signal characterization unit and a substance detection algorithm unit.

The multichannel signal acquisition unit is used for acquiring fluorescence intensity signals of a plurality of fluorescence channels of the fluorescent explosive, converting the fluorescence intensity signals into digital fluorescence signals and calculating a fluorescence response value of the fluorescent explosive. The fluorescence intensity signals alternately drive the 12-bit high-precision ADS acquisition chip through chip selection to finish the conversion from analog signals of the fluorescence signals of a plurality of channels to digital signals.

The signal preprocessing unit is used for eliminating the fluorescent background of the fluorescent response value to obtain a net fluorescent signal; and carrying out signal pretreatment on the net fluorescent signal to obtain a pretreated signal. The fluorescent background eliminates the fluorescent background signal superimposed by the fluorescent characteristic peak of the explosive, and can obtain better fluorescent spectrum data, so that the change of the fluorescent signal is more obvious, and the subsequent detection is more accurate.

The signal characterization unit is used for performing fluorescent signal compensation algorithm, K value solving algorithm and characteristic value characterization algorithm processing on the preprocessed signals to obtain the characteristic value z of the fluorescent explosive _i ′。

The substance detection algorithm unit is used for comparing the characteristic value z with the characteristic value comparison algorithm _i And (3) comparing the characteristic value Z with a characteristic value Z in a pre-established substance characteristic library, if a comparison result is obtained, obtaining the type of the fluorescent explosive, and if the comparison result is not obtained, indicating that the fluorescent explosive is not present.

In some embodiments, the explosives detection system further comprises: and the audible and visual alarm unit generates an audible and visual alarm signal when the types of fluorescent explosives are obtained, and the alarm module carries out audible or visual alarm according to the audible and visual alarm signal so as to prompt a user that the explosives exist and facilitate the subsequent removal of the explosives.

In some embodiments, the explosives detection system further comprises a build species library unit, the build species library unit comprising: the device comprises a room temperature characteristic value acquisition module, a high temperature characteristic value acquisition module, a low temperature characteristic value acquisition module and a fitting module.

The room temperature characteristic value acquisition module is used for acquiring a plurality of fluorescent explosives at room temperature T according to the acquired fluorescent explosives respectively _r Obtaining the characteristic value Z of the room temperature signal by the fluorescence intensity signals of a plurality of fluorescence channels _r 。

The high-temperature characteristic value acquisition module is used for acquiring a plurality of fluorescent explosives at a high temperature T according to the acquired fluorescent explosives respectively _h Obtaining high-temperature signal characteristic value Z by using fluorescence intensity signals of a plurality of fluorescence channels _h 。

The low-temperature characteristic value acquisition module is used for acquiring a plurality of fluorescent explosives at a low temperature T according to the acquired fluorescent explosives respectively _l Obtaining low-temperature signal characteristic value Z by using fluorescence intensity signals of a plurality of fluorescence channels _l 。

The fitting module is used for fitting the room temperature signal characteristic value Z _r Characteristic value Z of high temperature signal _h Low temperature signal characteristic value Z _l Fitting to a library of material characteristics.

The algorithms or steps used by each unit or module in the foregoing embodiments of the detection method have been described in the foregoing embodiments of the detection method, and for the same features, reference may be made to descriptions in related embodiments of the detection method, which are not repeated herein.

The following briefly describes the method of detecting explosives and the workflow of an explosives detection system.

The method and the system for detecting the explosives, provided by the embodiment of the application, adopt a fluorescent explosive detection instrument (also called a fluorescent explosion instrument) to detect whether the explosives exist in the substances to be detected in real time on site.

As shown in fig. 2, before collecting data, a work platform needs to be built and a work environment needs to be established. The working platform comprises a fluorescent explosive detection instrument, a temperature tester, an electronic computer and the like. The establishment of the working environment comprises the steps of connecting the components by adopting data wires and opening algorithm software generated according to the detection method on an electronic computer. And then opening the fluorescent explosive detection instrument and the temperature tester, and recording parameters of the two instruments. Because the present application takes into account the effect of environmental factors (e.g., temperature conditions, etc.) on the test results, it is desirable to record the instrument parameters.

Subsequently, the substance to be measured is brought into contact with the fluorescent material in the fluorescent explosive detection instrument, and then the process of detecting the explosive is started. If the substance to be detected does not contain explosive substances, the fluorescence of the fluorescent material is not changed. If the substance to be detected contains explosives, the explosives are contacted with the fluorescent material, so that the intensity of fluorescence emitted by the fluorescent material is changed, for example, the fluorescence is quenched or enhanced, whether the fluorescence is quenched or enhanced is different according to the types of the explosives, and the two are in corresponding relation, so that whether the substance to be detected contains the explosives and which types of the explosives are contained in the substance to be detected can be estimated according to the change of the fluorescence intensity.

When data are collected, an SPI of a singlechip is adopted to drive the ADS1255 sampling chip, the ADS1255 sampling chip is alternately driven in a mode of selecting a plurality of sampling chips through the SPI, multi-channel collection is carried out on fluorescent signals generated by fluorescent explosives, and analog signals of the fluorescent signals are converted into digital fluorescent signals.

After the digital fluorescent signal is obtained, the change value of the digital fluorescent signal after the explosive is introduced relative to the change value before the explosive is introduced, namely the fluorescent response value when the explosive is introduced. That is, the fluorescence response value is the absolute value of the difference between the fluorescence signal intensity after the explosive is introduced and the fluorescence signal intensity before the explosive is introduced.

The background noise of the fluorescence response values described above is then eliminated by means of a minimum value, a maximum value and an adaptive scaling window. And determining the maximum value and the minimum value of the signal to determine the window range of the characteristic peak of the signal so as to find the characteristic peak of the fluorescent explosive spectrum signal, then carrying out zero resetting treatment on the signal, and reducing the influence of the collar peak through self-adaptive signal scaling after the signal is zeroed. After the explosive is introduced and combined with the fluorescent material, the characteristic peaks of the fluorescent signal are overlapped with some background peaks to form a plurality of characteristic peaks, the characteristic peaks are overlapped with each other, and the collar peaks refer to the characteristic peaks adjacent to the characteristic peaks.

And then, carrying out signal preprocessing on the signal with the background noise removed, and normalizing the signal data to be within the range of 0-1 after obtaining the zero mean value of the signal set by using a zero mean value processing and normalization processing method to obtain the preprocessed signal. The method comprises the steps of reducing the dimension and the variation range of signals, reducing the interference of circuits or natural noise on the signals, and finally judging substances by adopting a substance detection algorithm according to the preprocessed signals.

According to the embodiment of the application, the fluorescent signals are compensated according to the temperature, humidity or air pressure conditions (mainly the temperature) of the environment where the fluorescent explosive detection instrument is located, so that the fluorescent explosive detection instrument is prevented from being located in different environments, and the signal response and the substance library have larger deviation when the explosive is detected, so that the detection precision is improved.

In addition, in order to quickly and accurately identify various explosives, a substance library is built for the explosives to be tested under different environmental conditions, meanwhile, when the explosives are identified, different explosives are pre-judged through a related algorithm, a preliminary identification result of the detected explosives is given, then specific explosives are identified through an inter-channel fluorescent signal alternating response identification algorithm, and erroneous judgment of the explosives is prevented.

The embodiment of the application also provides a method for establishing a substance characteristic library based on multichannel fluorescent explosive detection, which is characterized in that all environments required by the fluorescent explosive detection instrument are established by establishing a library establishment platform which is the same as parameters of the fluorescent explosive detection instrument, parameters of the instrument under each environment (such as low temperature, high temperature, room temperature and the like) are recorded, and the environmental parameters (such as low temperature, high temperature, room temperature and the like) are substituted into a formula of a characteristic curve formed by fitting. The characteristic values of the explosives under the environment are obtained by introducing different types of explosives in advance, then the environment in which the instrument is positioned is changed, the library construction operation is repeated, and finally the substance characteristic library for substance identification is obtained, wherein the substance characteristic library contains the corresponding relations between different environment parameters and the characteristic values of the different types of the explosives, so that the types of the corresponding explosives can be found in the substance characteristic library according to the newly measured characteristic values of the explosives and the corresponding environment parameters, and the detection of the types of the explosives is realized.

In fig. 2, the analysis substance library can obtain a pre-judging result of the type of the explosive, but the pre-judging result may deviate from the actual situation, so that the type of the explosive can be finally judged according to the fluorescent signal cross response recognition algorithm of each channel, and the detection result is obtained mainly by fixing the priority of the response of the explosive and the time of the peak of the explosive, and then comprehensively judging the characteristic value comparison result and the priority in the fixed time. Such an erroneous judgment prevention algorithm can improve the accuracy of judgment of the explosive species. If the final judgment result is the same as the pre-judgment result, the detection process is ended. And if the final judging result is different from the pre-judging result, adjusting the working environment, and carrying out detection again.

The flow of establishing a substance characteristic library in the embodiment of the application is shown in fig. 3, all environments required to work by the fluorescent explosive detection instrument are established by constructing a library establishment platform which is the same as parameters of the fluorescent explosive detection instrument, each environmental parameter is recorded, and the environmental parameters are substituted into a formula of a fitted characteristic curve. Aiming at different types of explosives, the characteristic value of the explosive in a certain specific environment is required to be obtained, then the environment of a fluorescent explosive detection instrument is changed, the operation of building a library is repeated, and finally the substance characteristic library for substance identification is obtained. In some embodiments of the present application, the environmental factors may include room temperature (T _r ) Low temperature (T) _l ＝T _r -20 ℃ C.) and high temperature (T) _h ＝T _r +40℃)。

In addition, environmental factors may also include air pressure values or humidity, etc. The air pressure value is divided into normal pressure (room temperature pressure P _r ) Low pressure (P) _l ) Or high pressure (P) _h ) Then the corresponding calculation formula is as follows:

normal pressure signal characteristic value Z _pr ：

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Low voltage signal characteristic value Z _pl ：

High voltage signal characteristic value Z _ph ：

The humidity value is divided into the current ambient humidity (H _r ) Low humidity (H) _l ) Or high humidity (H) _h ) Then the corresponding calculation formula is as follows:

current ambient humidity signal characteristic value Z _hr ：

Low humidity signal characteristic value Z _hl ：

High humidity signal characteristic value Z _ph ：

In addition, two parameters such as a temperature value and an air pressure value, an air pressure value and a humidity value may be considered at the same time, and in this case, each equation may be multiplied by the reciprocal of the corresponding parameter, for example, if the temperature value (room temperature) and the air pressure value (room pressure) are considered at the same time, the corresponding calculation formula is as follows:

signal characteristic value Z at normal temperature and normal pressure _tpr ：

The rest parameters are calculated as such.

In addition, three parameters of the temperature value, the air pressure value and the humidity value may be considered at the same time, and at the same time, the reciprocal of the three parameters is represented in the above respective formulas, for example, the temperature value (room temperature), the air pressure value (room pressure) and the humidity value (ambient humidity) are considered at the same time, and the corresponding calculation formulas are as follows:

normal temperature, normal pressure and normal humidity signal characteristic value Z _tphr ：

The other parameters of high temperature, low temperature, high pressure, low pressure, current environment humidity, low humidity and high humidity are calculated in the same way. If there are more parameters, the same processing is performed.

In summary, the present application provides an explosive detection method and detection system for a fluorescent explosive detection instrument, which eliminates background noise of a fluorescence spectrum by adopting a method of adaptively scaling a window, and then performs zero-mean and normalization preprocessing on the background noise, so as to reduce interference caused by a signal. By adopting a comprehensive judging method of characteristic value comparison, material pre-judgment and multi-channel signal alternating judgment, the fluorescent explosive detection instrument can detect and alarm the types of explosives more accurately and rapidly. The method also establishes a substance characteristic library for responding to the fluorescent explosive signals, and the substance characteristic library considers the influence of environmental factors, can identify the responses of different types of explosives under different environmental parameters, greatly improves the accuracy of judging the types of the explosives, and reduces the probability of misjudging the types of the explosives.

In the description of the present specification, a particular feature, structure, or characteristic may be combined in any suitable manner in one or more embodiments or examples.

The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of detecting explosives, comprising:

eliminating the fluorescence background of the fluorescence response value to obtain a net fluorescence signal;

performing fluorescent signal compensation algorithm, K value solving algorithm and characteristic value characterization algorithm processing on the preprocessed signals, and pre-judging the types of the fluorescent explosives according to characteristic value comparison algorithm;

The process of cancellation includes:

selecting a higher signal segment in the left return-to-zero signal segment and the right return-to-zero signal segment to multiply by a scaling factor f, and then respectively performing adaptive signal scaling to obtain the net fluorescent signal;

the formula of the proportionality coefficient f is as follows:

wherein f _max A and b are maximum values in the left signal segment and the right signal segment; and/or

The adaptive signal scales to: after the left zeroing signal segment or the right zeroing signal segment is multiplied by the scaling factor f, the following calculation is performed, respectively:

Wherein x is _I For each data value in the left zeroed signal segment or the right zeroed signal segment, n is the size of the data set of the left zeroed signal segment or the right zeroed signal segment;

the signal preprocessing comprises zero-mean processing and normalization processing;

the zero-mean processing method comprises the following steps:

according to the number num of the data of the net fluorescence signal and each data value x _I Obtaining the mean value u= (x) of the net fluorescence signal ₁ +x ₂ +…+x _i )/num；

Calculate standard deviation

Zero-mean processingObtaining a zero-mean signal;

the normalization processing method comprises the following steps:

obtaining a maximum value min (x _i ) And minimum value min (x _I ) Passing each data value of the zero-averaged signal throughScaling to between 0 and 1 to obtain the preprocessed signal;

the fluorescence signal compensation algorithm comprises: each data value x of the pre-processed signal _ii Substituting into fluorescent signal compensation formulaObtaining a compensated signal x _ii 'A'; t is the ambient temperature at the time of detection;

the K value solving algorithm is as followsSolving a K value; wherein I is _F Representing the original fluorescent signal, I _O Representing a fluorescent reference signal, A _T Represents the fluorescence wavelength at the current temperature, τ represents the fluorescence absorbance, x represents the multiplication, +. >Indicating the fluorescence quenching rate;

the characteristic value characterization algorithm is based on the compensated signal x _ii ' and K values calculate the characteristic value z of the fluorescent explosive _i ' the calculation formula is as follows: z _i ′*E[K*x _ii ′]-A|, where E represents the average value and A represents the compensated signal x _ii ' inverse of the formed signal matrix;

the eigenvalue comparison algorithm compares the eigenvalue z _i ' comparing the fluorescent explosive with a characteristic value Z in a pre-established substance characteristic library, if a comparison result is obtained, obtaining the type of the fluorescent explosive, and if the comparison result is not obtained, indicating that the fluorescent explosive is not present;

the method for establishing the substance characteristic library comprises the steps of obtaining a room temperature signal characteristic value Z _r Step (1) of obtaining a characteristic value Z of a high-temperature signal _h Step (a) of obtaining a low-temperature signal characteristic value Z _l Is a step of fitting;

the characteristic value Z of the room temperature signal is obtained _r The method comprises the following steps:

Calculating the room temperature signal characteristic value Z corresponding to the plurality of fluorescent explosives according to the following formula _r ：

Wherein Z is _r For the room temperature signal characteristic value, i is one data set of the pre-processed signal, j is another data set of the pre-processed signal which is re-measured after i, s is the time for obtaining the one data set, and the unit of s is min and T _r T is the temperature at room temperature _r Is given in units of deg.c;

the characteristic value Z of the high-temperature signal is obtained _h The method comprises the following steps:

calculating the characteristic value Z of the high-temperature signals corresponding to the multiple fluorescent explosives according to the following formula _h ：

Wherein Z is _h For the characteristic value of the high-temperature signal, i is one data set of the pre-processed signal, j is another data set of the pre-processed signal which is re-measured after i, s is the time for obtaining the one data set, and the unit of s is min and T _h T is the temperature at high temperature _h Is given in units of deg.c;

the characteristic value Z of the low-temperature signal is obtained _l The method comprises the following steps:

calculating the low-temperature signal characteristic value Z corresponding to the multiple fluorescent explosives according to the following formula _l ：

Wherein Z is _l For the characteristic value of the low-temperature signal, i is one data set of the pre-processed signal, j is another data set of the pre-processed signal which is re-measured after i, s is the time for obtaining the one data set, and the unit of s is min and T _l T is the temperature at low temperature _l Is given in units of deg.c;

the fitting step is to fit the room temperature signal characteristic value Z _r Said high temperature signal characteristic value Z _h The characteristic value Z of the low-temperature signal _l Fitting to a library of material characteristics.

2. The method of claim 1, wherein the plurality of ADS1255 sampling chips are alternately driven by an SPI chip-select drive to collect the fluorescent intensity signals of the plurality of fluorescent channels.

3. An explosives detection system, characterized in that the explosives detection system comprises:

the multi-channel signal acquisition unit acquires fluorescence intensity signals of a plurality of fluorescence channels of the fluorescent explosive, converts the fluorescence intensity signals into digital fluorescence signals and calculates a fluorescence response value of the fluorescent explosive;

the signal preprocessing unit is used for eliminating the fluorescent background of the fluorescent response value to obtain a net fluorescent signal; carrying out signal pretreatment on the net fluorescent signal to obtain a pretreated signal;

the signal characterization unit is used for performing fluorescent signal compensation algorithm, K value solving algorithm and characteristic value characterization algorithm processing on the preprocessed signals to obtain the characteristic value z of the fluorescent explosive _i ′；

A substance detection algorithm unit for comparing the characteristic value z by using a characteristic value comparison algorithm _i ' comparing the fluorescent explosive with a characteristic value Z in a pre-established substance characteristic library, if a comparison result is obtained, obtaining the type of the fluorescent explosive, and if the comparison result is not obtained, indicating that the fluorescent explosive is not present;

the process of cancellation includes:

the formula of the proportionality coefficient f is as follows:

the zero-mean processing method comprises the following steps:

Calculate standard deviation

Zero-mean processingObtaining a zero-mean signal;

the normalization processing method comprises the following steps:

the K value solving algorithm is as followsSolving a K value; wherein I is _F Representing the original fluorescent signal, I _O Representing a fluorescent reference signal, A _T Represents the fluorescence wavelength at the current temperature, τ represents the fluorescence absorbance, x represents the multiplication, +.>Indicating the fluorescence quenching rate;

4. An explosives detection system in accordance with claim 3, further comprising a central processing unit in communication with the multi-channel signal acquisition unit, the signal pre-processing unit, the signal characterization unit, the substance detection algorithm unit, respectively; and/or

The explosives detection system further includes: and the audible and visual alarm unit generates audible and visual alarm signals when the types of the fluorescent explosives are obtained.

5. An explosives detection system in accordance with claim 3, wherein the explosives detection system further comprises a build substance library unit, the build substance library unit comprising:

the room temperature characteristic value acquisition module is used for acquiring a plurality of fluorescent explosives at room temperature T according to the acquired fluorescent explosives respectively _r Obtaining the characteristic value Z of the room temperature signal by the fluorescence intensity signals of a plurality of fluorescence channels _r ；

Fitting module, which is used for fitting the room temperature signal characteristic value Z _r Said high temperature signal characteristic value Z _h The characteristic value Z of the low-temperature signal _l Fitting to a library of material characteristics.